Overview

Dataset statistics

Number of variables11
Number of observations322773
Missing cells0
Missing cells (%)0.0%
Duplicate rows3563
Duplicate rows (%)1.1%
Total size in memory27.1 MiB
Average record size in memory88.0 B

Variable types

Numeric11

Alerts

Dataset has 3563 (1.1%) duplicate rowsDuplicates
u is highly correlated with g and 6 other fieldsHigh correlation
g is highly correlated with u and 7 other fieldsHigh correlation
r is highly correlated with u and 7 other fieldsHigh correlation
i is highly correlated with u and 7 other fieldsHigh correlation
z is highly correlated with u and 7 other fieldsHigh correlation
uErr is highly correlated with u and 7 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with g and 7 other fieldsHigh correlation
zErr is highly correlated with gErr and 2 other fieldsHigh correlation
u is highly correlated with g and 5 other fieldsHigh correlation
g is highly correlated with u and 5 other fieldsHigh correlation
r is highly correlated with u and 5 other fieldsHigh correlation
i is highly correlated with u and 5 other fieldsHigh correlation
z is highly correlated with u and 5 other fieldsHigh correlation
uErr is highly correlated with u and 5 other fieldsHigh correlation
gErr is highly correlated with u and 6 other fieldsHigh correlation
rErr is highly correlated with gErr and 1 other fieldsHigh correlation
iErr is highly correlated with rErrHigh correlation
u is highly correlated with g and 5 other fieldsHigh correlation
g is highly correlated with u and 6 other fieldsHigh correlation
r is highly correlated with u and 6 other fieldsHigh correlation
i is highly correlated with u and 6 other fieldsHigh correlation
z is highly correlated with u and 6 other fieldsHigh correlation
uErr is highly correlated with u and 6 other fieldsHigh correlation
gErr is highly correlated with u and 7 other fieldsHigh correlation
rErr is highly correlated with g and 7 other fieldsHigh correlation
iErr is highly correlated with gErr and 2 other fieldsHigh correlation
zErr is highly correlated with rErr and 1 other fieldsHigh correlation
u is highly correlated with g and 4 other fieldsHigh correlation
g is highly correlated with u and 6 other fieldsHigh correlation
r is highly correlated with u and 6 other fieldsHigh correlation
i is highly correlated with u and 5 other fieldsHigh correlation
z is highly correlated with u and 3 other fieldsHigh correlation
uErr is highly correlated with uHigh correlation
gErr is highly correlated with g and 3 other fieldsHigh correlation
rErr is highly correlated with g and 4 other fieldsHigh correlation
iErr is highly correlated with g and 5 other fieldsHigh correlation
zErr is highly correlated with iErrHigh correlation
rErr is highly skewed (γ1 = 55.03254176) Skewed
iErr is highly skewed (γ1 = 90.4813831) Skewed
zErr is highly skewed (γ1 = 173.1138733) Skewed

Reproduction

Analysis started2022-02-27 19:47:21.898757
Analysis finished2022-02-27 19:47:54.580116
Duration32.68 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

ID
Real number (ℝ≥0)

Distinct319208
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.237664597 × 1018
Minimum1.23764588 × 1018
Maximum1.237680531 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:54.637402image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1.23764588 × 1018
5-th percentile1.237651497 × 1018
Q11.237658492 × 1018
median1.237663783 × 1018
Q31.237668298 × 1018
95-th percentile1.237679543 × 1018
Maximum1.237680531 × 1018
Range3.465177858 × 1013
Interquartile range (IQR)9.805951467 × 1012

Descriptive statistics

Standard deviation8.395528755 × 1012
Coefficient of variation (CV)6.783363419 × 10-6
Kurtosis-0.5681399988
Mean1.237664597 × 1018
Median Absolute Deviation (MAD)4.713715729 × 1012
Skewness0.3629541432
Sum2.025449374 × 1018
Variance7.048490308 × 1025
MonotonicityNot monotonic
2022-02-27T16:47:54.735294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.237663543 × 10184
 
< 0.1%
1.237663234 × 10182
 
< 0.1%
1.2376786 × 10182
 
< 0.1%
1.237657595 × 10182
 
< 0.1%
1.237660242 × 10182
 
< 0.1%
1.23766829 × 10182
 
< 0.1%
1.23766743 × 10182
 
< 0.1%
1.237648722 × 10182
 
< 0.1%
1.237648722 × 10182
 
< 0.1%
1.237678879 × 10182
 
< 0.1%
Other values (319198)322751
> 99.9%
ValueCountFrequency (%)
1.23764588 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
ValueCountFrequency (%)
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%

u
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct298932
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.9556061
Minimum11.754014
Maximum30.553564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:54.838591image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.754014
5-th percentile19.5969708
Q121.054209
median22.023914
Q322.774895
95-th percentile24.3006932
Maximum30.553564
Range18.79955
Interquartile range (IQR)1.720686

Descriptive statistics

Standard deviation1.437346452
Coefficient of variation (CV)0.06546603387
Kurtosis1.308288606
Mean21.9556061
Median Absolute Deviation (MAD)0.848509
Skewness0.01677101489
Sum7086676.847
Variance2.065964824
MonotonicityNot monotonic
2022-02-27T16:47:54.932850image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.163095
 
< 0.1%
22.2653585
 
< 0.1%
21.8332395
 
< 0.1%
23.0412965
 
< 0.1%
21.8129655
 
< 0.1%
21.6463284
 
< 0.1%
23.6025644
 
< 0.1%
21.9040164
 
< 0.1%
22.7508344
 
< 0.1%
23.1565934
 
< 0.1%
Other values (298922)322728
> 99.9%
ValueCountFrequency (%)
11.7540141
< 0.1%
12.3453271
< 0.1%
12.4588811
< 0.1%
13.2300871
< 0.1%
13.3569751
< 0.1%
13.5879131
< 0.1%
13.8825591
< 0.1%
13.9461341
< 0.1%
13.9848251
< 0.1%
14.0933311
< 0.1%
ValueCountFrequency (%)
30.5535641
< 0.1%
28.8272191
< 0.1%
28.8091771
< 0.1%
28.1116261
< 0.1%
27.9109551
< 0.1%
27.9089261
< 0.1%
27.7614361
< 0.1%
27.7462221
< 0.1%
27.7332861
< 0.1%
27.7127881
< 0.1%

g
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct299157
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.19373151
Minimum11.576696
Maximum30.612074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:55.026600image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.576696
5-th percentile17.9577148
Q119.195459
median20.370577
Q321.164747
95-th percentile22.1619626
Maximum30.612074
Range19.035378
Interquartile range (IQR)1.969288

Descriptive statistics

Standard deviation1.348269284
Coefficient of variation (CV)0.0667667233
Kurtosis0.2008340482
Mean20.19373151
Median Absolute Deviation (MAD)0.942066
Skewness-0.385922947
Sum6517991.299
Variance1.817830062
MonotonicityNot monotonic
2022-02-27T16:47:55.120350image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.9039425
 
< 0.1%
21.6402875
 
< 0.1%
21.5501085
 
< 0.1%
20.7723465
 
< 0.1%
21.3135785
 
< 0.1%
20.4169835
 
< 0.1%
21.0746364
 
< 0.1%
19.7492834
 
< 0.1%
20.7355984
 
< 0.1%
18.6404084
 
< 0.1%
Other values (299147)322727
> 99.9%
ValueCountFrequency (%)
11.5766961
< 0.1%
12.1299261
< 0.1%
12.276731
< 0.1%
12.5514651
< 0.1%
12.7043431
< 0.1%
12.9121421
< 0.1%
12.9225141
< 0.1%
12.9534351
< 0.1%
13.0144811
< 0.1%
13.0340891
< 0.1%
ValueCountFrequency (%)
30.6120741
< 0.1%
29.7172151
< 0.1%
27.4978581
< 0.1%
26.7244171
< 0.1%
26.6321871
< 0.1%
26.3971141
< 0.1%
26.1213511
< 0.1%
25.9690741
< 0.1%
25.8737431
< 0.1%
25.7411231
< 0.1%

r
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct296257
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.6947964
Minimum11.48799
Maximum29.998732
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:55.229725image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.48799
5-th percentile16.9483346
Q117.80587
median18.713923
Q319.446276
95-th percentile20.5818964
Maximum29.998732
Range18.510742
Interquartile range (IQR)1.640406

Descriptive statistics

Standard deviation1.15810765
Coefficient of variation (CV)0.06194812855
Kurtosis0.1326534155
Mean18.6947964
Median Absolute Deviation (MAD)0.817866
Skewness-0.07090050216
Sum6034175.517
Variance1.34121333
MonotonicityNot monotonic
2022-02-27T16:47:55.323472image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.6158035
 
< 0.1%
18.8624065
 
< 0.1%
18.7311125
 
< 0.1%
18.9512625
 
< 0.1%
18.7121225
 
< 0.1%
18.7347075
 
< 0.1%
18.9180414
 
< 0.1%
17.7029744
 
< 0.1%
18.8433174
 
< 0.1%
18.7618624
 
< 0.1%
Other values (296247)322727
> 99.9%
ValueCountFrequency (%)
11.487991
< 0.1%
11.5504751
< 0.1%
11.6575461
< 0.1%
11.7623351
< 0.1%
11.8844851
< 0.1%
11.9465471
< 0.1%
12.0181591
< 0.1%
12.223331
< 0.1%
12.2451321
< 0.1%
12.3915641
< 0.1%
ValueCountFrequency (%)
29.9987321
< 0.1%
29.3467521
< 0.1%
27.3994181
< 0.1%
25.8010751
< 0.1%
24.8350891
< 0.1%
24.7557831
< 0.1%
24.7557451
< 0.1%
24.7508451
< 0.1%
24.7499561
< 0.1%
24.7465081
< 0.1%

i
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct293614
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.06889016
Minimum11.023721
Maximum29.780376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:55.421313image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.023721
5-th percentile16.4923452
Q117.294764
median18.107769
Q318.757929
95-th percentile19.679493
Maximum29.780376
Range18.756655
Interquartile range (IQR)1.463165

Descriptive statistics

Standard deviation1.026973179
Coefficient of variation (CV)0.05683653889
Kurtosis0.5164648773
Mean18.06889016
Median Absolute Deviation (MAD)0.731504
Skewness-0.1562017704
Sum5832149.885
Variance1.054673909
MonotonicityNot monotonic
2022-02-27T16:47:55.577563image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.7415775
 
< 0.1%
17.4265845
 
< 0.1%
18.7493885
 
< 0.1%
18.3756075
 
< 0.1%
17.1207735
 
< 0.1%
18.4094095
 
< 0.1%
16.9439985
 
< 0.1%
18.051555
 
< 0.1%
18.3591795
 
< 0.1%
18.3720724
 
< 0.1%
Other values (293604)322724
> 99.9%
ValueCountFrequency (%)
11.0237211
< 0.1%
11.1717331
< 0.1%
11.223971
< 0.1%
11.3030941
< 0.1%
11.4867791
< 0.1%
11.8473641
< 0.1%
11.9138561
< 0.1%
11.922771
< 0.1%
11.9959911
< 0.1%
12.0199811
< 0.1%
ValueCountFrequency (%)
29.7803761
< 0.1%
27.967811
< 0.1%
25.7754781
< 0.1%
24.7235091
< 0.1%
24.5913961
< 0.1%
24.4108031
< 0.1%
24.4018841
< 0.1%
24.3399721
< 0.1%
24.3385661
< 0.1%
24.3312341
< 0.1%

z
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct292925
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.70271177
Minimum10.680226
Maximum28.568005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:55.671313image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum10.680226
5-th percentile16.1626814
Q116.960899
median17.735628
Q318.366991
95-th percentile19.2754992
Maximum28.568005
Range17.887779
Interquartile range (IQR)1.406092

Descriptive statistics

Standard deviation1.003498809
Coefficient of variation (CV)0.05668616322
Kurtosis0.7074093405
Mean17.70271177
Median Absolute Deviation (MAD)0.704908
Skewness-0.1104614452
Sum5713957.385
Variance1.007009859
MonotonicityNot monotonic
2022-02-27T16:47:55.765063image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.7455775
 
< 0.1%
17.2111785
 
< 0.1%
18.0954235
 
< 0.1%
18.5609895
 
< 0.1%
18.1574465
 
< 0.1%
16.8922825
 
< 0.1%
17.9405065
 
< 0.1%
17.0365494
 
< 0.1%
17.57934
 
< 0.1%
17.0988274
 
< 0.1%
Other values (292915)322726
> 99.9%
ValueCountFrequency (%)
10.6802261
< 0.1%
10.9023261
< 0.1%
10.9322171
< 0.1%
10.9714771
< 0.1%
11.1482761
< 0.1%
11.520191
< 0.1%
11.5408111
< 0.1%
11.547521
< 0.1%
11.5910191
< 0.1%
11.6875671
< 0.1%
ValueCountFrequency (%)
28.5680051
< 0.1%
27.7373771
< 0.1%
24.6665591
< 0.1%
24.3467181
< 0.1%
24.1179941
< 0.1%
23.6508061
< 0.1%
23.5537091
< 0.1%
23.5397721
< 0.1%
23.5218281
< 0.1%
23.4919871
< 0.1%

uErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct319208
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4093736363
Minimum0.01319976295
Maximum6.87985948
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:55.858813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.01319976295
5-th percentile0.06370328239
Q10.1791127415
median0.3379753453
Q30.5511080839
95-th percentile1.005467645
Maximum6.87985948
Range6.866659717
Interquartile range (IQR)0.3719953424

Descriptive statistics

Standard deviation0.3115871382
Coefficient of variation (CV)0.7611314227
Kurtosis6.775853907
Mean0.4093736363
Median Absolute Deviation (MAD)0.177190116
Skewness1.779470671
Sum132134.7567
Variance0.09708654468
MonotonicityNot monotonic
2022-02-27T16:47:55.955320image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.21687839354
 
< 0.1%
0.62442725162
 
< 0.1%
0.13149603362
 
< 0.1%
0.098194527912
 
< 0.1%
0.66594258622
 
< 0.1%
0.15667788882
 
< 0.1%
0.18390976132
 
< 0.1%
1.0369531822
 
< 0.1%
0.28164594032
 
< 0.1%
0.66111824252
 
< 0.1%
Other values (319198)322751
> 99.9%
ValueCountFrequency (%)
0.013199762951
< 0.1%
0.013351245231
< 0.1%
0.013734932251
< 0.1%
0.013781115711
< 0.1%
0.014017055791
< 0.1%
0.014196309771
< 0.1%
0.01429924121
< 0.1%
0.014378763161
< 0.1%
0.014417376561
< 0.1%
0.014555045111
< 0.1%
ValueCountFrequency (%)
6.879859481
< 0.1%
6.7429281431
< 0.1%
5.6244795851
< 0.1%
5.0871977181
< 0.1%
4.3853555731
< 0.1%
4.1876095441
< 0.1%
4.1051012171
< 0.1%
4.0095476021
< 0.1%
4.0002616391
< 0.1%
3.950198591
< 0.1%

gErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct319208
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09043704363
Minimum0.02266076487
Maximum6.429339305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:56.049069image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.02266076487
5-th percentile0.03282268764
Q10.04590849561
median0.07180088384
Q30.109452749
95-th percentile0.2038583536
Maximum6.429339305
Range6.40667854
Interquartile range (IQR)0.06354425342

Descriptive statistics

Standard deviation0.08013327711
Coefficient of variation (CV)0.8860669688
Kurtosis547.4661875
Mean0.09043704363
Median Absolute Deviation (MAD)0.0292055456
Skewness12.60740719
Sum29190.63588
Variance0.006421342101
MonotonicityNot monotonic
2022-02-27T16:47:56.142819image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.089124931364
 
< 0.1%
0.10544915282
 
< 0.1%
0.038242902122
 
< 0.1%
0.032502018242
 
< 0.1%
0.10423420522
 
< 0.1%
0.046229618112
 
< 0.1%
0.038008834242
 
< 0.1%
0.15298872962
 
< 0.1%
0.05903742332
 
< 0.1%
0.10131749552
 
< 0.1%
Other values (319198)322751
> 99.9%
ValueCountFrequency (%)
0.022660764871
< 0.1%
0.022828972741
< 0.1%
0.023102717821
< 0.1%
0.023115472781
< 0.1%
0.023144557781
< 0.1%
0.023233031931
< 0.1%
0.023315237751
< 0.1%
0.023337676521
< 0.1%
0.023396515781
< 0.1%
0.023398536521
< 0.1%
ValueCountFrequency (%)
6.4293393051
< 0.1%
6.2321475771
< 0.1%
5.3016349521
< 0.1%
5.2754343651
< 0.1%
4.7053938451
< 0.1%
4.1264177781
< 0.1%
3.927791421
< 0.1%
3.8854182221
< 0.1%
3.8027312941
< 0.1%
3.7364649551
< 0.1%

rErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct319208
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07348899497
Minimum0.03485844218
Maximum7.180163959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:56.236966image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.03485844218
5-th percentile0.04587236738
Q10.05382458467
median0.06389599803
Q30.0816330393
95-th percentile0.1338392608
Maximum7.180163959
Range7.145305517
Interquartile range (IQR)0.02780845462

Descriptive statistics

Standard deviation0.0422274164
Coefficient of variation (CV)0.5746087073
Kurtosis7054.017881
Mean0.07348899497
Median Absolute Deviation (MAD)0.01212842808
Skewness55.03254176
Sum23720.26337
Variance0.001783154696
MonotonicityNot monotonic
2022-02-27T16:47:56.330660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.059697414864
 
< 0.1%
0.077718996972
 
< 0.1%
0.050810768712
 
< 0.1%
0.046109851862
 
< 0.1%
0.088051273142
 
< 0.1%
0.054299794972
 
< 0.1%
0.04755556892
 
< 0.1%
0.11686206912
 
< 0.1%
0.056570023762
 
< 0.1%
0.068149089812
 
< 0.1%
Other values (319198)322751
> 99.9%
ValueCountFrequency (%)
0.034858442181
< 0.1%
0.035353798171
< 0.1%
0.035422473781
< 0.1%
0.035820037441
< 0.1%
0.035876852561
< 0.1%
0.03591975151
< 0.1%
0.03594233931
< 0.1%
0.035980422381
< 0.1%
0.035989162941
< 0.1%
0.036075722361
< 0.1%
ValueCountFrequency (%)
7.1801639591
< 0.1%
6.1650680511
< 0.1%
5.8551214741
< 0.1%
4.7793472441
< 0.1%
4.7638013361
< 0.1%
4.7427474771
< 0.1%
4.1996968841
< 0.1%
4.0542252631
< 0.1%
3.0811559271
< 0.1%
2.7849590561
< 0.1%

iErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct319208
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08095603334
Minimum0.03881203054
Maximum8.400347923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:56.436385image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.03881203054
5-th percentile0.05670971592
Q10.06526179428
median0.07463134987
Q30.08888451992
95-th percentile0.1233465462
Maximum8.400347923
Range8.361535893
Interquartile range (IQR)0.02362272564

Descriptive statistics

Standard deviation0.04799436577
Coefficient of variation (CV)0.5928448294
Kurtosis12336.67803
Mean0.08095603334
Median Absolute Deviation (MAD)0.01094209425
Skewness90.4813831
Sum26130.42175
Variance0.002303459146
MonotonicityNot monotonic
2022-02-27T16:47:56.522028image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.075844202294
 
< 0.1%
0.080109493072
 
< 0.1%
0.065294111252
 
< 0.1%
0.054842517772
 
< 0.1%
0.098595196632
 
< 0.1%
0.06936685942
 
< 0.1%
0.062186026792
 
< 0.1%
0.11318495762
 
< 0.1%
0.066459181732
 
< 0.1%
0.0734000882
 
< 0.1%
Other values (319198)322751
> 99.9%
ValueCountFrequency (%)
0.038812030541
< 0.1%
0.042700866651
< 0.1%
0.043017095221
< 0.1%
0.043129079441
< 0.1%
0.043481026761
< 0.1%
0.043634862671
< 0.1%
0.043775619511
< 0.1%
0.043859612291
< 0.1%
0.043978068121
< 0.1%
0.043981768051
< 0.1%
ValueCountFrequency (%)
8.4003479231
< 0.1%
8.0382233741
< 0.1%
7.8646871251
< 0.1%
6.489090481
< 0.1%
5.9628996521
< 0.1%
5.9539833471
< 0.1%
5.7991061361
< 0.1%
5.6970220251
< 0.1%
5.4225917771
< 0.1%
4.8295511191
< 0.1%

zErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct319208
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1168094872
Minimum0.04474935232
Maximum29.87530183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 MiB
2022-02-27T16:47:56.678290image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.04474935232
5-th percentile0.07541463688
Q10.09083066469
median0.106584126
Q30.1293160932
95-th percentile0.1848991822
Maximum29.87530183
Range29.83055248
Interquartile range (IQR)0.03848542855

Descriptive statistics

Standard deviation0.08975594519
Coefficient of variation (CV)0.7683960211
Kurtosis48683.61816
Mean0.1168094872
Median Absolute Deviation (MAD)0.01812983916
Skewness173.1138733
Sum37702.94861
Variance0.008056129696
MonotonicityNot monotonic
2022-02-27T16:47:56.772040image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11666170164
 
< 0.1%
0.13441275062
 
< 0.1%
0.095360752142
 
< 0.1%
0.077944796622
 
< 0.1%
0.14240545592
 
< 0.1%
0.090769475262
 
< 0.1%
0.087814578292
 
< 0.1%
0.17206968962
 
< 0.1%
0.099497505272
 
< 0.1%
0.09769502932
 
< 0.1%
Other values (319198)322751
> 99.9%
ValueCountFrequency (%)
0.044749352321
< 0.1%
0.045658706181
< 0.1%
0.048938930671
< 0.1%
0.049045324311
< 0.1%
0.049204802861
< 0.1%
0.049237841251
< 0.1%
0.049372547161
< 0.1%
0.049375802161
< 0.1%
0.04939584521
< 0.1%
0.049420440521
< 0.1%
ValueCountFrequency (%)
29.875301831
< 0.1%
20.344445131
< 0.1%
15.399468741
< 0.1%
9.0348090811
< 0.1%
8.5401514621
< 0.1%
4.747864871
< 0.1%
4.1962998581
< 0.1%
3.8071627221
< 0.1%
3.4932460111
< 0.1%
3.4924105461
< 0.1%

Interactions

2022-02-27T16:47:51.860470image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:31.655172image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:33.661327image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:35.736609image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:37.810062image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:39.833263image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:41.892200image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:43.964589image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:46.017616image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:47.928763image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:49.918683image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:52.043336image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:31.855234image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:33.846272image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:35.921585image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:37.996265image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:40.020066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:42.090348image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:44.149825image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:46.189182image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:48.112352image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:50.105439image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:52.228385image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:32.043345image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:34.029424image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:36.103159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:38.177911image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:40.202709image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:42.274562image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:44.333128image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:46.375401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:48.295905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:50.272602image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:52.393982image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:32.222652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:34.216960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:36.296345image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:38.377386image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:40.447161image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:42.459368image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:44.517716image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:46.555878image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:48.464054image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:50.437438image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:52.578102image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:32.407397image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:34.397213image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:36.472930image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:38.562936image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:40.621974image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:42.648576image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:44.701268image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:46.724179image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:48.712196image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:50.623514image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:52.747294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:32.593085image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:34.579826image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:36.656493image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:38.746298image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:40.805104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:42.827821image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:44.885763image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:46.908655image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:48.884566image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:50.789714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:52.932261image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:32.774524image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:34.827404image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:36.842039image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:38.935579image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:41.004030image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:43.011401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:45.069245image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:47.077218image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:49.064880image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:50.955633image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:53.098852image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:32.943739image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:35.015743image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:37.024787image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:39.113469image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:41.173928image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:43.246547image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:45.252167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:47.258318image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:49.234131image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:51.140090image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:53.276018image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:33.130442image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:35.200341image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:37.209269image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:39.282813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:41.356375image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:43.431227image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:45.421945image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:47.431348image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:49.402316image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:51.355730image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:53.449716image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:33.296913image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:35.385319image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:37.393062image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:39.478960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:41.541608image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:43.614050image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:45.604778image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:47.593804image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:49.587881image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:51.540184image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:53.613754image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:33.478646image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:35.556394image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:37.622125image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:39.648504image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:41.709173image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:43.797437image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:45.786520image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:47.761108image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:49.752170image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:47:51.695430image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-02-27T16:47:56.850165image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-02-27T16:47:56.966861image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-02-27T16:47:57.072719image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-02-27T16:47:57.182093image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-02-27T16:47:53.798708image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-02-27T16:47:54.030830image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

IDugrizuErrgErrrErriErrzErr
0123764594290511076822.37392420.30102318.91428618.43199718.1595170.3126670.0532210.0514270.0557310.075440
1123764594290556977322.49706620.95227219.39496018.85327918.4348090.5427270.1155570.0791840.0797350.109295
2123764594397832838122.67897621.65057819.88625319.21400518.8393230.5290010.1530880.0885230.0882520.112267
3123764594397852481921.03238318.86598617.56185917.13313116.8293060.1795820.0404550.0490650.0590500.074079
4123764594397852488921.57626720.21681018.49581917.97449517.6144410.2571840.0676140.0560280.0632110.076636
5123764594397859051821.16587419.13066917.66862717.22780616.9494090.2679510.0553520.0592080.0700570.091337
6123764594397859076123.82711822.26603320.51006919.85076919.4928150.7256610.1998550.0989390.0937190.125562
7123764594397865605121.89442820.38026818.85330818.34680917.9446680.3507420.0760740.0613990.0661410.161078
8123764594397872150222.07780120.38406019.02260218.58708618.2957130.3426190.0654580.0581500.0650430.079621
9123764594397872154621.39077020.25034018.93605218.48809218.2062680.2449760.0732160.0657400.0726600.089991

Last rows

IDugrizuErrgErrrErriErrzErr
322763123768053081525578024.33683421.41881219.51132618.80689418.3568591.0484350.1143280.0785060.0889510.102196
322764123768053081571398123.45782721.23199819.37774318.68882918.2109780.9605360.1240570.0822710.0932210.116708
322765123768053081650074822.75956221.76936920.68083619.65621919.2881390.7859100.2172120.2110300.1819290.238482
322766123768053081663198123.90333222.32110820.87495019.79347219.2833941.1683630.2791900.2065760.1635260.209199
322767123768053081741839022.27361120.69907019.87421619.12998218.7572460.7197860.1322740.1749940.1866240.240496
322768123768053081748311725.54130021.28424119.37867418.57955918.1373000.9045650.2176600.1520720.1660660.193869
322769123768053081918741126.02027321.84404420.21909719.30853518.8929420.4811630.1998160.1420570.1390650.175742
322770123768053081925321422.18565923.07504721.33887520.10450619.5790480.2870640.3488830.2045750.1468780.196234
322771123768053135442025325.84915922.01780520.32897019.44092418.8436490.4127660.2210410.1470980.1408610.159505
322772123768053135632050121.98962421.69380820.04319019.10477318.5510730.3472560.1347240.1044780.1003720.123098

Duplicate rows

Most frequently occurring

IDugrizuErrgErrrErriErrzErr# duplicates
1731123766354260256460121.02669118.85767017.33858116.84001916.4499090.2168780.0891250.0596970.0758440.1166624
0123764594290602844921.85052920.18495418.96590418.44527118.0761970.5814250.1122050.0908560.0871330.1096432
1123764679652723985220.61661118.67450917.40710416.91176616.5741810.1163710.0359720.0532320.0700180.1116342
2123764870297085585923.43465021.32988019.62007118.84243018.4832210.7687410.1224610.0802140.0814420.1074592
3123764870297262530923.72026621.79726019.91053619.11218118.7830510.7874210.1601220.0834110.0803410.1164652
4123764870297577100121.23249120.07767918.53403917.84629617.4066750.1759360.0709830.0658200.0741970.0977462
5123764870298199748722.86277421.17665719.87861419.15980918.8600100.3647180.0824660.0670820.0724870.0914692
6123764870351369046121.84996819.70611618.33368117.69356017.2939870.2715680.0514020.0559690.0621580.0852112
7123764870352188287923.20710221.38642319.83950619.05857318.6655770.5899110.1010360.0727750.0684030.0938292
8123764870352417641520.68453019.18692417.80713117.32796916.9732570.1405500.0474280.0541870.0614580.0810212